Validation of the UNESP-Botucatu unidimensional composite pain scale for assessing postoperative pain in cattle

Background: The recognition and measurement of pain in cattle are important in determining the necessity for and efficacy of analgesic intervention. The aim of this study was to record behaviour and determine the validity and reliability of an instrument to assess acute pain in 40 cattle subjected to orchiectomy after sedation with xylazine and local anaesthesia. The animals were filmed before and after orchiectomy to record behaviour. The pain scale was based on previous studies, on a pilot study and on analysis of the camera footage. Three blinded observers and a local observer assessed the edited films obtained during the preoperative and postoperative periods, before and after rescue analgesia and 24 hours after surgery. Re-evaluation was performed one month after the first analysis. Criterion validity (agreement) and item-total correlation using Spearman's coefficient were employed to refine the scale. Based on factor analysis, a unidimensional scale was adopted. Results: The internal consistency of the data was excellent after refinement (Cronbach's a coefficient = 0.866). There was a high correlation (p < 0.001) between the proposed scale and the visual analogue, simple descriptive and numerical rating scales. The construct validity and responsiveness were confirmed by the increase and decrease in pain scores after surgery and rescue analgesia, respectively (p < 0.001). Inter-and intra-observer reliability ranged from moderate to very good. The optimal cut-off point for rescue analgesia was > 4, and analysis of the area under the curve (AUC = 0.963) showed excellent discriminatory ability. Conclusion: The UNESP-Botucatu unidimensional pain scale for assessing acute postoperative pain in cattle is a valid, reliable and responsive instrument with excellent internal consistency and discriminatory ability. The cut-off point for rescue analgesia provides an additional tool for guiding analgesic therapy.